Research ArticleHemisphere differences in response of sea surface temperature and sea ice to precession and obliquity
Introduction
As one of the most important drivers of the climate system, the incoming solar radiation (insolation), depends largely on the three astronomical parameters: eccentricity, obliquity and climatic precession (Berger, 1976, Berger, 1978). The total energy received by the whole Earth over one year is only a function of eccentricity, while obliquity and precession can modify the latitudinal-seasonal distribution of insolation (Berger, 1988; Loutre et al., 2004; Berger et al., 2010). Astronomical theory of paleoclimate has been generally accepted and widely used in the research of paleoclimate, especially during the last 40 years (Hay et al., 1976), and the astronomical signals have been found in plenty of geological records like deep-sea sediments, continental archives and ice cores.
With the richness of the geological records, much attention has been paid on the relationship between different climatic variables and the astronomical parameters. For example, the relationship between SST and the astronomical parameters has been investigated based on marine records from the Pacific (eg. de Garidel-Thoron et al., 2005), Atlantic (eg. Lawrence et al., 2009) and Indian Ocean (eg. Howard and Prell, 1992). The response of other climatic variables to astronomical forcing has also been discussed, like sea ice (eg. Cronin et al., 2013), vegetation (eg. Joannin et al., 2011; Sanchez Goñi et al., 2016; Oliveira et al., 2018) and the Asian monsoon (eg. Cheng et al., 2016). Numerous climate model simulations have also been used to understand the response of the climate system to the astronomical forcing. For example, Earth system models of intermediate complexity (EMICs) (eg. Ganopolski and Calov, 2011; Holden et al., 2011; Yin and Berger, 2015) have been used to perform long transient simulations to study the climate response to varied astronomical parameters, GHG and NH ice sheets over many glacial-interglacial cycles. More complex atmosphere-ocean general circulations models, such as HadCM3 (Singarayer et al., 2011), have been used to perform snapshot experiments to study the response of one or more components of the climate system to changes in insolation. Both proxy and modeling studies show that the climate response to the astronomical forcing depends strongly on regions and on different climatic variables.
On hemisphere scale, evidence from both paleoclimate records and simulations shows that the two hemispheres seem to respond differently to obliquity and precession. As far as sea ice is concerned, Lo et al. (2018) found that the autumn sea ice extent was governed by precession-dominated insolation when the atmospheric CO2 concentrations ranging from 190 to 260 ppmv during the last 130 ka in the central Okhotsk Sea. Cronin et al. (2013) reconstructed the sea ice extent during the last 600 ka in western Arctic Ocean and found that the sea ice varied mainly at precessional and obliquity frequencies with precession playing a more important role. In the Southern Ocean, Wolff et al. (2006) reconstructed winter sea ice extent using the ssNa flux over the past eight glacial cycles, and found that its variation was dominated by periodicities on time scales of 80–120 ka although the obliquity and precessional components can also be found. For SST, the reconstructed results also show an obvious difference between the NH and SH. Besides the 100 ka periodicity, the SST reconstructions show a clear obliquity signal in both hemispheres, but the precessional signal is much stronger in the NH than in the SH (Martrat et al., 2007; Bard and Rickaby, 2009). Based on snapshot and 10-times accelerated transient simulations, Yin and Berger, 2012, Yin and Berger, 2015 found that in general the NH climate responds more to precession whereas the SH responds more to obliquity, but in-depth analyses on internal processes and feedbacks are still needed. In addition, Timmermann et al. (2014) investigated the response of the SH climate to obliquity and CO2 using a series of snapshot simulations and a 5-times accelerated transient simulation. They found that the SH westerlies were mainly controlled by the obliquity cycle and the temperature changes in Antarctica were determined by the combined effect of shortwave obliquity forcing, GHG forcing, and meridional heat transport.
In spite of many existing studies, the different response of the climate system to obliquity and precession between the two hemispheres is still not very clear. This is mainly due to: (1) in the geological records, it is not straightforward to distinguish the impact of the astronomical parameters from other forcings, like GHG and ice sheets, because they can contain the same periodicities; and (2) the numerical simulations, which focus on understanding the response of the climate system to obliquity and precession and especially the differences between the two hemispheres, are still scarce. Thus, there is a need to investigate the response of the different climatic variables to obliquity and precession using long and continuous transient simulations.
Here we focus on understanding the relative importance of precession and obliquity on two important components in the climate system, sea ice and SST, in both hemispheres as well as the internal processes and feedbacks involved to explain the differences between the two hemispheres. Our study is based on a transient simulation using the model LOVECLIM (see section 2 for model description). Although LOVECLIM is classified as an Earth system model of intermediate complexity, its complexity is on the top of this kind of models and thus it can not be used easily to run a transient simulation spanning several glacial cycles. Therefore, in our study, we choose the time interval between 511 and 417 ka BP which covers the interglacial peak of MIS-13, the glacial MIS-12 and the beginning of MIS-11. There are three reasons to choose this period. First, this period includes both high and low values of eccentricity which leads to both large and small amplitude of variations in precession and therefore in daily insolation. In particular, it covers MIS-11 with near-zero eccentricity which has been considered as an astronomical analogue of our present interglacial (Loutre and Berger, 2003). Second, this period includes both situations where precession minimum and obliquity maximum are in-phase and are anti-phase (Fig. 1) (the phase relationship between precession and obliquity could be critical for the climate system (Yin and Berger, 2010, Yin and Berger, 2015)). Third, this period covers the Mid-Brunhes Transition or Event (MBT or MBE) that is characterized by relatively warmer interglacials after about 430 ka BP than before (eg. Jansen et al., 1986; Jouzel et al., 2007). The causes proposed to explain the MBE include for example astronomical forcing (Pisias and Rea, 1988; Yin, 2013) and a major ice-sheet expansion during MIS-12 (Bard and Rickaby, 2009). In this study, we don't intend to investigate the MBE, but our results and simulation might be useful for other studies concerning this topic.
Section snippets
Model and experiment design
LOVECLIM is a three dimension Earth system Model of Intermediate Complexity (Goosse et al., 2010). In our study, the atmosphere (ECBilt), the terrestrial biosphere (VECODE), and the ocean and sea ice (CLIO) are interactively coupled. ECBilt is a spectral atmospheric model with truncature T21, which corresponds approximately to a horizontal resolution of 5.625° × 5.625°. It has three vertical layers and its dynamics are governed by the quasi-geostrophic potential vorticity. VECODE is a
Sea ice
Fig. 1 shows clearly that the responses of the Arctic and Southern Ocean sea ice to the astronomical forcing are different. In the Arctic, the variation of the annual mean sea ice is highly correlated with precession, while in the Southern Ocean, it is highly correlated with obliquity. In order to quantify the relative weight of each astronomical parameter on the sea ice variations, multiple linear regression analyses (using the standardized values of the variables) are performed. The results (
Conclusions
In this study, the different responses of the SST and sea ice to precession and obliquity between the two hemispheres are investigated through a transient simulation with the LOVECLIM model.
Our results show that the responses are different between the two hemispheres. The Arctic sea ice is highly correlated with precession, while the Southern Ocean sea ice is highly correlated with obliquity. In the Arctic, the variation of the annual mean sea ice is dominated by the variation in local summer
Acknowledgments
This work is supported by the Fonds de la Recherche Scientifique-FNRS (F.R.S.-FNRS) under grant MIS F.4529.18 and the National Natural Science Foundation of China (Grant Nos. 41690114 and 41888101). Q.Z. Yin is Research Associate F.R.S.-FNRS. Z.P. Wu thanks Dr. Feng Shi and Rui Zhang for discussion. We also thank the anonymous reviewers for their constructive comments. Computational resources have been provided by the supercomputing facilities of the Université catholique de Louvain (CISM/UCL)
Declaration of Competing Interests
None.
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